Setting up data

Data from Human Mortality Database and Human Fertility Database was used to calculate birth rates. This was tidied to give Under-18 rates:

Code Country Year rate GDPperCap MF_ratio MobilePhones UrbanPop
1 Austria 1985 8.63 9172.10 1.04 0.13 64.31
1 Austria 1986 8.44 13083.07 1.04 0.25 64.04
1 Austria 1987 8.19 16392.77 1.03 0.34 63.77
1 Austria 1988 7.89 17578.62 1.04 0.48 63.50
1 Austria 1989 8.58 17468.95 1.04 0.66 63.23
1 Austria 1990 8.80 21680.99 1.04 0.95 62.96

Abortion estimates were added to give Under-20 rates:

Code Country Year pRate rate GDPperCap MF_ratio MobilePhones UrbanPop
2 Czechia 1990 71.17 46.01 3917.16 1.05 0.00 75.22
2 Czechia 1991 72.91 47.52 2878.72 1.05 0.01 75.16
2 Czechia 1992 69.70 45.14 3352.03 1.05 0.04 75.03
2 Czechia 1993 62.31 42.91 3931.74 1.05 0.14 74.90
2 Czechia 1994 46.97 32.33 4601.95 1.04 0.29 74.77
2 Czechia 1995 36.53 24.43 5788.15 1.04 0.47 74.64

Iterating through year combinations

For each comparison, I iterated through all combinations of years as special predictors to minimise MSPE (whilst prioritising fewest groupings). For example, for the under-18 basic model with years as special predictors:

it_u18_rateSp <- testSynthIterations(
  yrs = 1985:1998,
  pred = "rate",
  data = synthData_u18[,1:4],
  ccodes = u_18_ccodes,
  n = 4,
  predictors = NULL,
  time.optimise = 1985:1998
) %>%
  arrange(groups, mspe)

Generating Synthetic Control models for all Under-18 comparisons

Model 1: Rate only as predictor

England vs Synthetic Control

Weights

Country Weight
Lithuania 0.648
Italy 0.179
Norway 0.105
United States of America 0.056
Poland 0.005
Czechia 0.001
Estonia 0.001
Finland 0.001
Germany 0.001
Portugal 0.001
Switzerland 0.001
Austria 0.000
Denmark 0.000
France 0.000
Hungary 0.000
Iceland 0.000
Netherlands 0.000
Northern Ireland 0.000
Scotland 0.000
Slovenia 0.000
Spain 0.000
Sweden 0.000

Placebo testing by country and time

Model 2: GDP as predictor

England vs Synthetic Control

Weights

Country Weight
Norway 0.502
United States of America 0.325
Sweden 0.173
Austria 0.000
Denmark 0.000
Finland 0.000
France 0.000
Germany 0.000
Iceland 0.000
Italy 0.000
Netherlands 0.000
Portugal 0.000
Spain 0.000
Switzerland 0.000

Placebo testing by country and time

Model 3: All predictors

England vs Synthetic Control

Weights

Country Weight
Norway 0.482
United States of America 0.322
Sweden 0.177
Finland 0.019
Austria 0.000
Denmark 0.000
France 0.000
Germany 0.000
Iceland 0.000
Italy 0.000
Netherlands 0.000
Portugal 0.000
Spain 0.000
Switzerland 0.000

Placebo testing by country and time

Generating Synthetic Control models for all Under-20 comparisons

Model 1: England vs Synthetic Control

England vs Synthetic Control

Weights

Country Weight
Italy 0.723
United States of America 0.211
Netherlands 0.066
Czechia 0.000
Denmark 0.000
Estonia 0.000
Finland 0.000
France 0.000
Germany 0.000
Hungary 0.000
Iceland 0.000
Lithuania 0.000
New Zealand 0.000
Norway 0.000
Poland 0.000
Portugal 0.000
Scotland 0.000
Slovenia 0.000
Spain 0.000
Sweden 0.000
Switzerland 0.000

Placebo testing by country and time

Model 2: GDP as predictor

England vs Synthetic Control

Weights

Country Weight
Netherlands 0.581
United States of America 0.419
Czechia 0.000
Denmark 0.000
Finland 0.000
France 0.000
Germany 0.000
Hungary 0.000
Iceland 0.000
Italy 0.000
New Zealand 0.000
Norway 0.000
Poland 0.000
Portugal 0.000
Spain 0.000
Sweden 0.000
Switzerland 0.000

Placebo testing by country and time

Model 3: All predictors

England vs Synthetic Control

Weights

Country Weight
Netherlands 0.581
United States of America 0.419
Czechia 0.000
Denmark 0.000
Finland 0.000
France 0.000
Germany 0.000
Hungary 0.000
Iceland 0.000
Italy 0.000
Norway 0.000
Portugal 0.000
Spain 0.000
Sweden 0.000
Switzerland 0.000

Placebo testing by country and time